Triple

T22373818
Position Surface form Disambiguated ID Type / Status
Subject Vite E553105 entity
Predicate supportsLanguage P2177 FINISHED
Object Less NE NERFINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Less | Statement: [Vite, supportsLanguage, Less]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Less
Context triple: [Vite, supportsLanguage, Less]
  • A. Less chosen
    Less is a dynamic stylesheet language that extends CSS with features like variables, mixins, and functions to make writing and maintaining styles more efficient.
  • B. the Less
    The Less is an epithet traditionally used to distinguish James the Less, one of the Twelve Apostles of Jesus, from other early Christian figures named James.
  • C. Few
    Few is an English-language surname borne by various notable individuals, including American politician and Founding Father William Few.
  • D. Little
    Little is a common English surname borne by numerous notable individuals across fields such as sports, politics, and the arts.
  • E. Little
    Little is a 2019 fantasy-comedy film in which a domineering tech executive is magically transformed into her younger self, forcing her to relive middle school and confront her past behavior.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69e11e4c03248190a26a5060ea6973ee completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15806b534819083716c2b090ede42 completed April 29, 2026, 12:59 a.m.
Created at: April 16, 2026, 8:45 p.m.